MicroRNAs (miRNAs) play multiple roles in tumor biology. Interestingly, reports from multiple groups suggest that miRNA targets may be coupled through competitive stoichiometric sequestration. Specifically, computational models predicted and experimental assays confirmed that miRNA activity is dependent on miRNA target abundance, and consequently, changes in the abundance of some miRNA targets lead to changes to the regulation and abundance of their other targets. The resulting indirect regulatory influence between miRNA targets resembles competition and has been dubbed competitive endogenous RNA (ceRNA). Recent studies have questioned the physiological relevance of ceRNA interactions, our ability to accurately predict these interactions, and the number of genes that are impacted by ceRNA interactions in specific cellular contexts. To address these concerns, we reverse engineered ceRNA networks (ceRNETs) in breast and prostate adenocarcinomas using context-specific TCGA profiles, and tested whether ceRNA interactions can predict the effects of RNAi-mediated gene silencing perturbations in PC3 and MCF7 cells._ENREF_22 Our results, based on tests of thousands of inferred ceRNA interactions that are predicted to alter hundreds of cancer genes in each of the two tumor contexts, confirmed statistically significant effects for half of the predicted targets. Our results suggest that the expression of a significant fraction of cancer genes may be regulated by ceRNA interactions in each of the two tumor contexts.

The determination of long non-coding RNA (lncRNA) function is a major challenge in RNA biology with applications to basic, translational, and medical research. We developed BigHorn to computationally infer lncRNA-DNA interactions that mediate transcription and chromatin-remodeling factor activity. Its accurate inference enabled the identification of lncRNAs that coordinately regulate both the transcriptional and post-transcriptional processing of their targets. These lncRNAs may act as molecular chaperones, regulating the stability and translation of mRNAs they helped transcribe, leading to tightly coupled expression profiles. Our analysis suggests that lncRNAs regulate cancer genes across tumor contexts, thus propagating the effects of non-coding alterations to effectively dysregulate cancer programs. As a proof of principle, we studied the regulation of DICER1, a cancer gene that plays a key role in microRNA biogenesis, by the lncRNA ZFAS1. We showed that ZFAS1 helps activate DICER1 transcription and block its mRNA degradation to phenomimic DICER1 and regulate its target microRNAs.